Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions-Reference-Cited by-同舟云学术

Assessment of Accuracy of an Artificial Intelligence Algorithm to Detect Melanoma in Images of Skin Lesions

Published:2019-10-16 Issue:10 Volume:2 Page:e1913436
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Phillips Michael¹²,Marsden Helen³,Jaffe Wayne⁴,Matin Rubeta N.⁵,Wali Gorav N.⁵,Greenhalgh Jack³,McGrath Emily⁶,James Rob⁶,Ladoyanni Evmorfia⁷,Bewley Anthony⁸⁹,Argenziano Giuseppe¹⁰,Palamaras Ioulios¹¹

Affiliation:

1. Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia

2. Centre for Medical Research, University of Western Australia, Perth, Western Australia, Australia

3. Skin Analytics Limited, London, United Kingdom

4. Royal Stoke University Hospital, University Hospital North Midlands, Stoke, United Kingdom

5. Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom

6. Royal Devon and Exeter NHS Foundation Trust, Exeter, United Kingdom

7. Dudley Group NHS Foundation Trust, Corbett Hospital, Stourbridge, United Kingdom

8. Barts Health, London, United Kingdom

9. Queen Mary School of Medicine, University of London, London, United Kingdom

10. Dermatology Unit, University of Campania, Naples, Italy

11. Barnet and Chase Farm Hospitals, Royal Free NHS Foundation Trust, London, United Kingdom

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2752995/phillips_2019_oi_190513.pdf

Reference32 articles.

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3. Diagnosing and managing cutaneous pigmented lesions: primary care physicians versus dermatologists.;Chen;J Gen Intern Med,2006

4. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults.;Dinnes;Cochrane Database Syst Rev,2018

5. Reflectance confocal microscopy for diagnosing cutaneous melanoma in adults.;Dinnes;Cochrane Database Syst Rev,2018

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